Fix median sampling error if only 1 distinct value (#377)

This commit addresses an exception that occurs during calculation of the
median sampling error if the data containts only 1 distinct value.

Error being addressed:
    The data appears to lie in a lower-dimensional subspace of the space
    in which it is expressed. This has resulted in a singular data
    covariance matrix, which cannot be treated using the algorithms
    implemented in `gaussian_kde`. Consider performing principle
    component analysis / dimensionality reduction and using
    `gaussian_kde` with the transformed data.

nannyml/sampling_error/summary_stats.py

@@ -7,6 +7,7 @@
 
 import numpy as np
 import pandas as pd
+import warnings
 from scipy.stats import gaussian_kde, moment
 
 logger = getLogger(__name__)
@@ -80,8 +81,13 @@ def summary_stats_median_sampling_error_components(col: pd.Series) -> Tuple:
     (median, pdf(median): Tuple[np.ndarray]
     """
     median = col.median()
-    kernel = gaussian_kde(col)
-    fmedian = kernel.evaluate(median)[0]
+    try:
+        kernel = gaussian_kde(col)
+        fmedian = kernel.evaluate(median)[0]
+    except np.linalg.LinAlgError as ex:
+        logger.warning("Suppressing LinAlgError in summary_stats_median_sampling_error_components: %r", ex)
+        warnings.warn(f"Suppressing LinAlgError in summary_stats_median_sampling_error_components: {ex}")
+        fmedian = np.inf
     return (median, fmedian)